Are Electronic Notifications in Imaging Order Communication Systems an Effective Means of Changing Clinicians' Behaviour?
Bibliographic record
Abstract
Introduction Order Communication Systems (Ordercomms) are computer applications used to enter diagnostic and therapeutic patient care orders and view test results. These electronic systems allow the integration of Clinical Decision Support Systems (CDSS). CDSS are computer applications designed to aid clinicians in making diagnostic and therapeutic decisions in patient care (e.g. can notify clinicians of best practice guidelines when requesting investigations or prescribing medications). The aims of this study were to determine whether electronic notifications (via Ordercomms) are effective in improving clinician compliance with the Ottawa Rules in plain radiographs requesting for ankle trauma, and the efficacy of electronic notifications in reducing inappropriate imaging requests. Methods The Ottawa Rules are a globally validated clinical decision tool with a sensitivity of 99%-100% for ankle fractures. When used, they can reduce the number of unnecessary radiographs by 30%-40%. Importantly, the Royal College of Radiologists stipulates that a patient must fulfill the Ottawa Rules in order to proceed with a plain radiograph of the ankle in trauma. A retrospective analysis of 366 plain ankle radiographs was performed to exclude bony injury in the emergency department between February and March 2018. Information gathered included patient demographics, the request form completed by the emergency department clinician, and radiology report. A pop-up reminder was then implemented on the electronic requesting system to prompt clinicians to apply the Ottawa Ankle Rules and document their plain radiograph request accordingly. Following the intervention, a further 473 plain radiographs were analysed in the same way over a three-month period (April-June 2018). Results In the two months prior to the intervention, 366 plain radiographs were performed for ankle trauma. Of these, 45.1% fulfilled the Ottawa Rules. In the three months following our intervention, 473 plain radiographs were carried out. There was no significant increase in the percentage of requests fulfilling the Ottawa Rules (45.7%). Unnecessary radiographs (those which did not fulfill the Ottawa Rules and consequently showed no fracture) also showed no change. The data demonstrates that the electronic reminder asking individuals to apply and document the Ottawa Rules appropriately had no impact on the imaging requesting behaviour, and subsequently on the number of unnecessary plain radiographs. Conclusion Electronic notifications in Order Communication Systems did not change clinicians' behaviour in this specific circumstance. This study has implications for electronic notifications in prescribing systems and pathology requesting systems. Further research is needed to determine if the findings are replicated with other imaging types.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.047 | 0.298 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".